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Estimation in the Swedish LFS – an example of combining survey data from independent samples Martin Axelson & Frida Videll Statistics Sweden e-mail: firstname.lastname@scb.se
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Outline The current sampling design for the Swedish LFS Combining data from independent samples – some theory Estimation in the Swedish LFS 9th Workshop on Labour Force Survey Methodology 2
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The current sampling design for the Swedish LFS – project 1 Carried out by Statistics Sweden in 2008 In response to increased interest in groups outside or with a weak attachment to the labour market Goal: To suggest a cost-efficient way to secure better statistics for domains of particular interest Suggestion: Combine data from two samples One drawn according to the design in use One drawn according to a design constructed with high precision for specific parameters and domains of study in mind. 9th Workshop on Labour Force Survey Methodology 3
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The current sampling design for the Swedish LFS – project 2 9th Workshop on Labour Force Survey Methodology 4
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9th Workshop on Labour Force Survey Methodology 5
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Stratification after Region Sex Age Born in Sweden (Y/N) Not working (Y/N) Not working Derived using available register information Important register: Longitudinal integration database for health insurance and labour market studies Prediction of “Not working” during the reference week at the individual level 9th Workshop on Labour Force Survey Methodology 6
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9th Workshop on Labour Force Survey Methodology 7
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Combining data from independent samples – some notation 9th Workshop on Labour Force Survey Methodology 8
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Combining data from independent samples – explicit weighting 9th Workshop on Labour Force Survey Methodology 9
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Combining data from independent samples – implicit weighting 9th Workshop on Labour Force Survey Methodology 10
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Combining data from independent samples – some relevant facts 9th Workshop on Labour Force Survey Methodology 11
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Estimation in the Swedish LFS – project 1 The possible gains in precision presented by project 1 were unrealistic Numerical results on expected gain based on (almost) optimal explicit weighting of GREG- estimators Such weighting amounts to using parameter specific weight systems, i.e., different weights are used for different parameters, which NSIs typically try hard to avoid 9th Workshop on Labour Force Survey Methodology 12
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Estimation in the Swedish LFS – project 2 9th Workshop on Labour Force Survey Methodology 13
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Estimation in the Swedish LFS – project 3 9th Workshop on Labour Force Survey Methodology 14
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Estimation in the Swedish LFS – today 9th Workshop on Labour Force Survey Methodology 15
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Estimation in the Swedish LFS – examples of precision gains 9th Workshop on Labour Force Survey Methodology 16. Expected gain 20 0.91 40 0.85 60 0.79 80 0.75 100 0.71
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Estimation in the Swedish LFS – examples of precision gains 9th Workshop on Labour Force Survey Methodology 17.
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Estimation in the Swedish LFS – examples of precision gains 9th Workshop on Labour Force Survey Methodology 18
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Estimation in the Swedish LFS – concluding remarks 9th Workshop on Labour Force Survey Methodology 19
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Finding solutions to methodological challenges – reflections from a methodologist Typically requires using (challenging) theory and methodology Theory and practice must go hand in hand – let implementation be part of the challenge Should be seen as an investment, as the short-term cost is expected to be followed by long-term savings Sampling design and estimation are best treated together, given the strong dependency between them 9th Workshop on Labour Force Survey Methodology 20
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